Michael D. Rugg

36.0k total citations · 9 hit papers
292 papers, 26.2k citations indexed

About

Michael D. Rugg is a scholar working on Cognitive Neuroscience, Developmental and Educational Psychology and Social Psychology. According to data from OpenAlex, Michael D. Rugg has authored 292 papers receiving a total of 26.2k indexed citations (citations by other indexed papers that have themselves been cited), including 269 papers in Cognitive Neuroscience, 41 papers in Developmental and Educational Psychology and 26 papers in Social Psychology. Recurrent topics in Michael D. Rugg's work include Memory and Neural Mechanisms (170 papers), Memory Processes and Influences (168 papers) and Neural and Behavioral Psychology Studies (118 papers). Michael D. Rugg is often cited by papers focused on Memory and Neural Mechanisms (170 papers), Memory Processes and Influences (168 papers) and Neural and Behavioral Psychology Studies (118 papers). Michael D. Rugg collaborates with scholars based in United Kingdom, United States and Germany. Michael D. Rugg's co-authors include Richard N. Henson, Kaia L. Vilberg, Raymond J. Dolan, Leun J. Otten, Tim Curran, Michael Coles, Kevin Allan, Melina R. Uncapher, Andrew P. Yonelinas and Jeffrey D. Johnson and has published in prestigious journals such as Nature, Neuron and Journal of Neuroscience.

In The Last Decade

Michael D. Rugg

288 papers receiving 25.6k citations

Hit Papers

Guidelines for using human event‐related potentials to st... 1995 2026 2005 2015 2000 2007 1999 2018 2005 500 1000 1.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Guidelines for using human event‐related potentials to study cognition: Recording standards and publication criteria
    2000 1.6k citations Michael D. Rugg et al. Psychophysiology profile →
  2. Event-related potentials and recognition memory
    2007 1.0k citations Michael D. Rugg, Tim Curran Trends in Cognitive Sciences profile →
  3. Recollection and Familiarity in Recognition Memory: An Event-Related Functional Magnetic Resonance Imaging Study
    1999 689 citations Richard N. Henson, Michael D. Rugg et al. Journal of Neuroscience profile →
  4. Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing
    2018 688 citations Michael D. Rugg et al. profile →
  5. Separating the Brain Regions Involved in Recollection and Familiarity in Recognition Memory
    2005 647 citations Michael D. Rugg et al. Journal of Neuroscience profile →
  6. Electrophysiology of Mind: Event-Related Brain Potentials and Cognition
    1995 603 citations Michael D. Rugg et al. profile →
  7. Dissociation of the neural correlates of implicit and explicit memory
    1998 594 citations Michael D. Rugg, Ruth E. Mark et al. Nature profile →
  8. Brain networks underlying episodic memory retrieval
    2012 531 citations Michael D. Rugg et al. profile →
  9. Memory retrieval and the parietal cortex: A review of evidence from a dual-process perspective
    2008 508 citations Michael D. Rugg et al. Neuropsychologia profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael D. Rugg United Kingdom 85 23.8k 4.0k 3.6k 2.8k 1.9k 292 26.2k
Andrew P. Yonelinas United States 71 21.0k 0.9× 3.5k 0.9× 2.5k 0.7× 4.2k 1.5× 3.5k 1.9× 204 24.0k
Thomas F. Münte Germany 73 13.8k 0.6× 3.9k 1.0× 3.7k 1.0× 2.5k 0.9× 1.3k 0.7× 474 19.2k
Anna C. Nobre United Kingdom 84 21.9k 0.9× 2.1k 0.5× 4.6k 1.3× 2.0k 0.7× 1.1k 0.6× 336 25.3k
Neal J. Cohen United States 64 12.6k 0.5× 3.0k 0.8× 2.1k 0.6× 1.4k 0.5× 3.3k 1.8× 192 18.5k
D. Yves von Cramon Germany 86 17.0k 0.7× 2.6k 0.6× 3.6k 1.0× 2.9k 1.1× 992 0.5× 241 20.8k
Tim Shallice United Kingdom 74 21.6k 0.9× 6.8k 1.7× 5.2k 1.5× 3.7k 1.3× 1.0k 0.6× 227 27.8k
Elizabeth K. Warrington United Kingdom 80 19.4k 0.8× 7.2k 1.8× 4.0k 1.1× 3.1k 1.1× 1.4k 0.8× 237 24.9k
Gabriele Gratton United States 61 16.1k 0.7× 2.2k 0.5× 4.0k 1.1× 2.0k 0.7× 977 0.5× 174 20.4k
Robert T. Knight United States 96 28.6k 1.2× 2.3k 0.6× 5.1k 1.4× 3.4k 1.2× 4.4k 2.3× 381 33.9k
Roberto Cabeza United States 85 25.5k 1.1× 3.5k 0.9× 4.7k 1.3× 2.8k 1.0× 2.1k 1.1× 203 31.0k

Countries citing papers authored by Michael D. Rugg

Since Specialization
Citations

This map shows the geographic impact of Michael D. Rugg's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael D. Rugg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael D. Rugg more than expected).

Fields of papers citing papers by Michael D. Rugg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael D. Rugg. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael D. Rugg. The network helps show where Michael D. Rugg may publish in the future.

Co-authorship network of co-authors of Michael D. Rugg

This figure shows the co-authorship network connecting the top 25 collaborators of Michael D. Rugg. A scholar is included among the top collaborators of Michael D. Rugg based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael D. Rugg. Michael D. Rugg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Rugg, Michael D., et al.. (2023). A meta-analysis of event-related potential correlates of recognition memory. Brain and Cognition. 170. 106028–106028. 1 indexed citations
2.
Hill, Paul F., Marianne de Chastelaine, & Michael D. Rugg. (2022). Patterns of retrieval-related cortico-striatal connectivity are stable across the adult lifespan. Cerebral Cortex. 33(8). 4542–4552. 2 indexed citations
3.
Koen, Joshua D., et al.. (2021). The hippocampus shows an own‐age bias during unfamiliar face viewing. European Journal of Neuroscience. 54(11). 7876–7885. 1 indexed citations
4.
Koen, Joshua D., et al.. (2020). Effects of Age on Prestimulus Neural Activity Predictive of Successful Memory Encoding: An fMRI Study. Cerebral Cortex. 31(2). 917–932. 4 indexed citations
5.
Hill, Paul F., et al.. (2020). Age Differences In Retrieval-Related Reinstatement Reflect Age-Related Dedifferentiation At Encoding. Cerebral Cortex. 31(1). 106–122. 27 indexed citations
6.
Chastelaine, Marianne de, et al.. (2020). Neural correlates of post-retrieval monitoring in older adults are preserved under divided attention, but are decoupled from memory performance. Neurobiology of Aging. 97. 106–119. 7 indexed citations
7.
Rugg, Michael D., et al.. (2020). Direct brain recordings identify hippocampal and cortical networks that distinguish successful versus failed episodic memory retrieval. Neuropsychologia. 147. 107595–107595. 8 indexed citations
8.
Koen, Joshua D., et al.. (2018). The Relationship between Age, Neural Differentiation, and Memory Performance. Journal of Neuroscience. 39(1). 149–162. 73 indexed citations
9.
10.
Rugg, Michael D., Sandhitsu R. Das, Joel M. Stein, et al.. (2017). Theta band power increases in the posterior hippocampus predict successful episodic memory encoding in humans. Hippocampus. 27(10). 1040–1053. 72 indexed citations
11.
Wang, Tracy H., Jeffrey D. Johnson, Marianne de Chastelaine, Brian E. Donley, & Michael D. Rugg. (2015). The Effects of Age on the Neural Correlates of Recollection Success, Recollection-Related Cortical Reinstatement, and Post-Retrieval Monitoring. Cerebral Cortex. 26(4). 1698–1714. 52 indexed citations
12.
Johnson, Jeffrey D., L. Tugan Muftuler, & Michael D. Rugg. (2008). Multiple repetitions reveal functionally and anatomically distinct patterns of hippocampal activity during continuous recognition memory. Hippocampus. 18(10). 975–980. 58 indexed citations
13.
Rugg, Michael D. & Tim Curran. (2007). Event-related potentials and recognition memory. Trends in Cognitive Sciences. 11(6). 251–257. 1001 indexed citations breakdown →
14.
Herron, Jane E. & Michael D. Rugg. (2003). Strategic influences on recollection in the exclusion task: Electrophysiological evidence. Psychonomic Bulletin & Review. 10(3). 703–710. 70 indexed citations
15.
Phillips, Christophe, Michael D. Rugg, & Karl Friston. (2002). Anatomically Informed Basis Functions for EEG Source Localization: Combining Functional and Anatomical Constraints. NeuroImage. 16(3). 678–695. 142 indexed citations
16.
Henson, Richard N., Tim Shallice, Michael D. Rugg, Paul C. Fletcher, & Raymond J. Dolan. (2001). 15. Functional imaging dissociations within right prefrontal cortex during episodic memory retrieval. UCL Discovery (University College London). 5 indexed citations
17.
Rugg, Michael D., et al.. (1998). Dissociation of the neural correlates of implicit and explicit memory. Nature. 392(6676). 595–598. 594 indexed citations breakdown →
18.
Rugg, Michael D., Paul C. Fletcher, Kevin Allan, et al.. (1998). Neural Correlates of Memory Retrieval during Recognition Memory and Cued Recall. NeuroImage. 8(3). 262–273. 123 indexed citations
19.
Rugg, Michael D., et al.. (1997). ERP repetition effects in indirect and direct tasks: Effects of age and interitem lag. Psychophysiology. 34(5). 572–586. 90 indexed citations
20.
Rugg, Michael D., et al.. (1993). Cognitive brain potentials in a three-stimulus auditory “oddball” task after closed head injury. Neuropsychologia. 31(4). 373–393. 47 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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